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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Análise de Cenários Baseada em Agentes×Dinâmica de Sistemas×
ÁreaSimulaçãoSimulação
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1990s–2000s1961
Autor originalAxelrod, R.; Schoemaker, P. J. H. (combined lineage)Jay W. Forrester
TipoHybrid simulation–scenario methodContinuous simulation / feedback modelling
Fonte seminalAxelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Outros nomesABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABMstock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation
Relacionados43
ResumoAgent-based scenario analysis embeds agent-based simulation models inside a structured scenario planning framework. Researchers define two to four contrasting future scenarios, configure agent populations and environmental rules to reflect each scenario's assumptions, run the simulation under each condition, and compare emergent outcomes. This makes it possible to explore how decentralized individual behaviors aggregate into system-level consequences under radically different futures.System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research.
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ScholarGateComparar métodos: Agent-based scenario analysis · System Dynamics. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare